Writing data avoiding write conflicts in a dispersed storage network

ABSTRACT

A method begins by a by a first device of a dispersed storage network (DSN) sending a set of write revision requests to storage units of the DSN. The method continues with one of the storage units generating a write revision response regarding a potential write conflict issue. The method continues with the first device receiving the write revision responses to produce a set of received write revision responses and interpreting the set of received write revision responses to determine whether a write conflict issue exists. When the write conflict issue exists, the method continues with the first device issuing a set of write roll back requests to the storage units. When the write conflict issue does not exist, the method continues with the first device issuing a set of next phase write requests to the storage units regarding storing revised encoded data slices.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. §119(e) to the following U.S. Provisional patent applicationwhich is hereby incorporated herein by reference in its entirety andmade part of the present U.S. Utility patent application for allpurposes:

1. U.S. Provisional Application Ser. No. 61/700,691, entitled “UPDATINGA DISPERSED STORAGE AND TASK NETWORK INDEX,” (Attorney Docket No.CS01213), filed Sep. 13, 2012, pending.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work station, video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a diagram illustrating an example of an index structure inaccordance with the present invention;

FIG. 40B is a diagram illustrating an example of an index node structurein accordance with the present invention;

FIG. 40C is a diagram illustrating an example of a leaf node structurein accordance with the present invention;

FIG. 40D is a diagram illustrating another example of an index structurein accordance with the present invention;

FIG. 40E is a diagram illustrating an example of a metadata objectstructure in accordance with the present invention;

FIG. 40F is a flowchart illustrating an example of updating a cachedindex node in accordance with the present invention;

FIG. 41 is a flowchart illustrating an example of updating an index nodein accordance with the present invention;

FIG. 42 is a flowchart illustrating an example of adjusting an indexnode update time period in accordance with the present invention;

FIGS. 43A-B are schematic block diagrams of embodiments of a dispersedstorage network (DSN) in accordance with the present invention;

FIGS. 43C-D are timing diagrams illustrating examples of timing ofwriting data in accordance with the present invention;

FIGS. 43E-H are timing diagrams illustrating examples of timing ofresponses to writing of data in accordance with the present invention;

FIGS. 43I-K are timing diagrams illustrating examples of writing data toa set of storage units in accordance with the present invention;

FIG. 43L is a flowchart illustrating an example of storing data inaccordance with the present invention;

FIGS. 44A-B are schematic block diagrams of more embodiments of adispersed storage network (DSN) in accordance with the presentinvention;

FIGS. 44C-E are timing diagrams illustrating examples of timing ofreading data in accordance with the present invention;

FIGS. 44F-H are timing diagrams illustrating examples of reading datafrom a set of storage units in accordance with the present invention;

FIG. 44I is a flowchart illustrating an example of reading data inaccordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 45B is a flowchart illustrating an example of authorizing an accessrequest in accordance with the present invention;

FIG. 46A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 46B is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIG. 47 is a flowchart illustrating an example of rebuilding data inaccordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;and

FIG. 48B is a flowchart illustrating another example of storing data inaccordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsincludes, but is not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terra-Bytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terra-Bytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terra-Bytes) into 100,000 data segments, each being 1 Giga-Byte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The group selecting module 114 outputs the slice groupings96 to the corresponding DST execution units 36 via the network 24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, wherein in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of datasegments 156 for a given data partition, the slicing module outputs aplurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the first set of encoded data slices include errorcorrection data based on the first-third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—)1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—)2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—)3) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—)4, whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—)5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or andthe other analog and/or digital processing circuitry), availability ofthe processing resources, etc. If the controller 86 determines that theDT execution module(s) 90 have sufficient capabilities, it generatestask control information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results may 102 also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identity of other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step executing the task in accordance with the task controlinformation 176, the DT execution module 90 retrieves the encoded slicesfrom memory 88. The DT execution module 90 then reconstructs contiguousdata blocks of a data partition. As shown for this example,reconstructed contiguous data blocks of data partition 1 include datablocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbounded DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data 122. The DS error decoding module 182decodes, in accordance with DS error encoding parameters, the encodeddata slices per data partition 122 to produce data partitions 120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—)1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of a de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupselection module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 218 of the datasegments into pillars of slices 216. The number of pillars correspondsto the pillar width of the DS error encoding parameters. In thisexample, the distributed task control module 118 facilitates the storagerequest.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Salomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terra-Bytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distributions modules location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few terra-bytes or more),addressing information of Addr_(—)1_AA, and DS parameters of 3/5;SEG_(—)1; and SLC_(—)1. In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., 3/5 for the first data entry), segmentsecurity information (e.g., SEG_(—)1), per slice security information(e.g., SLC_(—)1), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of 3/5; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1_(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or and other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words or/or phrases intranslated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task 1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compare to IDerrors (ordered after task 1-4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words).

Task 1_(—)3 (e.g., translate) includes task execution information asbeing non-ordered (i.e., is independent), having DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate data partitions2_(—)1 through 2_(—)4 and having DT execution modules 1_(—)2, 2_(—)2,3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5 through 2_zto produce task 1_(—)3 intermediate results (R1-3, which is thetranslated data). In this example, the data partitions are grouped,where different sets of DT execution modules perform a distributedsub-task (or task) on each data partition group, which allows forfurther parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3_z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2 'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3_z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_(—)1 through R1-3_z) to produce task 3_(—)2 intermediate results(R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2_m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g.,1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the 1^(st) allocated setof DT execution modules executes task 1_(—)4 to produce partial results102 (e.g., through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terra-Byte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a diagram illustrating an example of a distributed indexstructure 350 of one or more indexes utilized to access a data object ofone or more data objects 1_(—)1 through 1_w, 3_(—)1 through 3_w, 4_(—)1through 4_w, etc., where at least some of the one or more data objectsare stored in at least one of a distributed storage and task network(DSTN) and a dispersed storage network (DSN), and where a data object ofthe one or more data objects is dispersed storage error encoded toproduce a plurality sets of encoded data slices, and where the pluralityof sets of encoded data slices are stored in the DSN (e.g., and/or DSTN)utilizing a common source name (e.g., DSN address). The source nameprovides a DSTN and/or DSN address including one or more of vaultidentifier (ID) (e.g., such a vault ID associates a portion of storageresources of the DSN with one or more DSN user devices), a vaultgeneration indicator (e.g., identify a vault generation of one or moreof generations), and an object number that corresponds to the dataobject (e.g., a random number assigned to the data object when the dataobject is stored in the DSN).

The distributed index structure 350 includes at least two nodesrepresented in the index structure as nodes associated with two or morenode levels. One or more nodes of the at least two nodes of thedistributed index structure 350 may be dispersed storage error encodedto produce one or more sets of encoded index slices. The one or moresets of encoded index slices may be stored in at least one of a localmemory, a DSN memory, and a distributed storage and task network (DSTN)module. For example, each node of a 100 node distributed index structureare individually dispersed storage error encoded to produce at least 100sets of encoded index slices for storage in the DSTN module. As anotherexample, the 100 node index structure is aggregated into one index fileand the index file is dispersed storage error encoded to produce a setof encoded index slices for storage in the DSTN module.

Each node of the at least two nodes includes at least one of an indexnode and a leaf node. One index node of the at least two nodes includesa root index node. Alternatively, the distributed index structure 350includes just one node, wherein the one node is a leaf node and wherethe leaf node is a root node. The distributed index structure 350 mayinclude any number of index nodes, any number of leaf nodes, and anynumber of node levels. Each level of the any number of node levelsincludes nodes of a common node type. For example, all nodes of nodelevel 4 are leaf nodes and all nodes of node level 3 are index nodes. Asanother example, as illustrated, the distributed index structure 350includes eight index nodes and eight leaf nodes, where the eight indexnodes are organized in three node levels, where a first node levelincludes a root index node 1_(—)1, a second node level includes indexnodes 2_(—)1, 2_(—)2, and 2_(—)3, and a third node level includes indexnodes 3_(—)1, 3_(—)2, 3_(—)3, 3_(—)4, and 3_(—)5, and where the eightleaf nodes are organized in a last (e.g., fourth) node level, where thelast node level includes leaf nodes 4_(—)1, 4_(—)2, 4_(—)3, 4_(—)4,4_(—)5, 4_(—)6, 4_(—)7, and 4_(—)8.

Each data object of the one more data objects is associated with atleast one index key per distributed index structure of the one or moredistributed indexes, where the index key includes a searchable elementof the distributed index and may be utilized to locate the data objectin accordance with key type traits. An index key type of an index keyincludes a category of the index key (e.g. string integer, etc.). Anindex key type exhibits traits. Each index key is associated with one ormore key type traits (e.g., for an associated index structure), where akey type traits includes one or more of a type indicator, a traitindicator, a comparing function (e.g., defining how an associate indexkey of this type should be compared, such as sorting and/ormanipulation, to other such index keys), a serialization function (e.g.,encoding function for storage), a de-serialization function (e.g.,decoding function for retrieval), and an absolute minimum value of theindex key.

Each leaf node of the at least two nodes may be associated with one ormore data objects. The association includes at least one of, for eachdata object of the one more data objects, storing an index keyassociated with the data object in the leaf node, storing a source nameassociated with the data object in the leaf node, and storing the dataobject in the leaf node. For example, leaf node 4_(—)2 includes a dataobject 4_(—)2 and an index key associated with data object 4_(—)2. Asanother example, leaf node 4_(—)3 includes source names associated withdata object 3_(—)1 through 3_w and index keys associated with dataobject 3_(—)1 through 3_w. Each leaf node is associated with a minimumindex key, where the minimum index key is a minimum value of one or moreindex keys associated with the one or more data objects in accordancewith the key type traits (e.g., sorted utilizing a comparing function ofthe key type traits to identify the minimum value).

Each leaf node is a child in a parent-child relationship with one indexnode, where the one index node is a parent in the parent-childrelationship. Each child node has one parent node and each parent nodehas one or more child nodes. The one index node (e.g., parent node)stores a minimum index key associated with the leaf node (e.g., childnode). As such, a parent node stores a minimum index key for each childnode of the one or more child nodes. Two index nodes may form aparent-child relationship. In such a parent-child relationship, aparent-child node pair is represented in the index structure with aparent node of the parent-child relationship associated with a parentnode level that is one level above in the index structure than a childnode level associated with a child node of the parent-childrelationship.

A leaf node is a sibling node of another leaf node when a minimum indexkey associated with the leaf node is ordered greater than a last minimumindex key associated with the other leaf node, where the last minimumindex key associated with the leaf node is sorted above any other lastminimum index keys associated with any other lower order leaf nodes andwhere the minimum index key associated with the leaf node is orderedless than any other minimum index keys associated with any other higherorder leaf nodes. A sibling node of a node is represented in the indexstructure on a common level with the node and one node position to theright. A last node on the far right of a node level has a no sibling(e.g., null sibling). All other nodes, if any, other than a last farright node, of a common node level have a sibling node. For example,leaf node 4_(—)2 is a sibling node to leaf node 4_(—)1, leaf node 4_(—)3is a sibling node to leaf node 4_(—)2, etc., leaf node 4_(—)8 is asibling node to leaf node 4_(—)7 and leaf node 4_(—)8 has no siblingnode.

Each index node of the at least two nodes may be associated with one ormore child nodes. Such a child node includes at least one of anotherindex node or a leaf node. The association includes, for each child nodeof the one more child nodes, storing a minimum index key associated withthe child node in the index node and storing a source name associatedwith the child node in the index node. Each child node is associatedwith a minimum index key, where the minimum index key is a minimum valueof one or more index keys associated with the child node (e.g., theminimum index key is a minimum value of one or more index keysassociated with one or more children nodes of the child node or one ormore data objects of the child node in accordance with the key typetraits, sorted utilizing a comparing function of the key type traits toidentify the minimum value when the child node is a leaf node). Forexample, index node 3_(—)2 includes a minimum index key (e.g., of dataobject 3_(—)1) and source name associated with leaf node 4_(—)3. Asanother example, index node 3_(—)3 includes a minimum index key andsource name associated with leaf node 4_(—)4 and another minimum indexkey and another source name associated with leaf node 4_(—)5. As yetanother example, index node 2_(—)3 includes a minimum index key andsource name associated with index node 3_(—)4 and minimum index key andanother source name associated with index node 3_(—)5.

An index node is a sibling node of another index node when a minimumindex key associated with the index node is ordered greater than a lastminimum index key associated with the other index node, where the lastminimum index key associated with the index node is sorted above anyother last minimum index keys associated with any other lower orderindex nodes and where the minimum index key associated with the indexnode is ordered less than any other minimum index keys associated withany other higher order index nodes. For example, index node 3_(—)2 is asibling node to index node 3_(—)1, index node 3_(—)3 is a sibling nodeto index node 3_(—)2, etc., index node 3_(—)6 is a sibling node to indexnode 3_(—)5 and index node 3_(—)6 has no sibling node.

FIG. 40B is a diagram illustrating an example of an index node structure352 for an index node that includes index node information 356, siblingnode information 358, and children node information 360. Alternatively,there is no sibling node information 358 when the index node has nosibling node. The index node information 356 includes one or more of anindex node source name field 362, an index node revision field 364, anda node type field 366. Inclusion and/or use of the index node sourcename field 362 and the index node revision field 364 is optional.

The sibling node information 358 includes a sibling node source namefield 368, a sibling minimum index key field 370, and a sibling key typetraits field 372. Inclusion and/or use of the sibling key type traitsfield 372 is optional. The children node information 360 includes one ormore child node information sections 374, 376, etc. corresponding toeach child node of the index node. Each child node information sectionof the one or more child node information sections includes acorresponding child node source name field 378, a corresponding childminimum index key field 380, and a corresponding child key type traitsfield 382. For example, the corresponding child node source name field378 of a child 1 node information section 374 includes a child 1 nodesource name entry. Inclusion and/or use of the corresponding child keytype traits field 382 is optional.

The index node source name field 362 may include an index node dispersedstorage network (DSN) address 354 entry (e.g., source name)corresponding to a storage location for the index node. The index noderevision field 364 may include an index node revision entrycorresponding to a revision number of information contained in the indexnode. Use of the index node revision field 364 enables generating two ormore similar indexes while saving each revision of the two or moresimilar indexes. The node type field 366 includes a node type entry,where the node type entry indicates whether the node is a leaf node ornot a leaf node. The node type indicates that the node is not a leafnode when the node is the index node.

The sibling node source name field 368 includes a sibling node sourcename entry (e.g., sibling node DSN address) corresponding to where asibling node is stored in a DSN memory and/or a distributed storage andtask network (DSTN) module when the index node has the sibling node as asibling. The sibling node is another index node when the index node hasthe sibling. The sibling node source name field 368 may include a nullentry when the index node does not have a sibling. The sibling minimumindex key field 370 includes a sibling of minimum index keycorresponding to the sibling node when the index node has the siblingnode as the sibling. The sibling key type traits field 372 may includesibling key type traits corresponding to the sibling node when the indexnode has the sibling node as the sibling and when the sibling key typetraits field is utilized. Alternatively, index structure metadata mayinclude key type traits utilized globally for each node of the indexstructure.

The index structure metadata may include one or more of key type traitsto be utilized for all nodes of a corresponding index, key type traitsto be utilized for all index nodes of the corresponding index, key typetraits to be utilized for all leaf nodes of the corresponding index, asource name of a root node of the index structure, a maximum number ofindex structure levels, a minimum number of the next level structures, amaximum number of elements per index structure level, a minimum numberof elements per index structure level, and index revision number, and anindex name. The index structure metadata may be utilized for one or moreof accessing the index, generating the index, updating the index, savingthe index, deleting portions of the index, adding a portion to theindex, cloning a portion of the index, and searching through the index.The index structure metadata may be stored in one or more of a localmemory, one or more nodes of the index structure, and as encodedmetadata slices in at least one of the DSTN module and the DSN memory.

The child node source name field 378 includes a child node source nameentry (e.g., child node DSN address) corresponding to a storage locationfor the child node. For example, a child 1 node source name field 378 ofa child 1 node information section 374 includes a child 1 node sourcename. The child minimum index key field 380 includes a child minimumindex key corresponding to the child node. For example, a child 1minimum index key field 380 of the child 1 node information section 374includes a child 1 minimum index key. The child key type traits field382 may include child key type traits corresponding to the child nodewhen the index node has the child node as the child and when the childkey type traits field is utilized. Alternatively, the index structuremetadata may include key type traits utilized globally for each node ofthe index structure.

FIG. 40C is a diagram illustrating an example of a leaf node structure384 that includes leaf node information 388, sibling node information358, and data information 392. Alternatively, there is no sibling nodeinformation 358 when the leaf node has no sibling node. The leaf nodeinformation 388 includes one or more of a leaf node source name field394, a leaf node revision field 396, and a node type field 366.Inclusion and/or use of the leaf node source name field 394 and the leafnode revision field 396 is optional. The sibling node information 358includes a sibling node source name field 368, a sibling minimum indexkey field 370, and a sibling key type traits field 372. Inclusion and/oruse of the sibling key type traits field 372 is optional. The datainformation 392 includes one or more data information sections 398, 400,etc. corresponding to each data object associated with the leaf node.Alternatively, the data information 392 includes null information whenno data object is presently associated with the leaf node. Each datainformation section of the one or more data information sectionsincludes a corresponding data (e.g., data object) source name or datafield 402, a corresponding data index key field 404, and a correspondingdata key type traits field 406. For example, the corresponding datasource name field 402 of a data 1 node information section 398 includesa data 1 source name entry. Inclusion and/or use of the correspondingdata key type traits field 406 is optional.

The leaf node source name field 394 may include a leaf node source nameentry (e.g., leaf node distributed storage and task network (DSTN)address and/or a dispersed storage network (DSN) address) correspondingto a storage location of the leaf node. The leaf node revision field 396may include a leaf node revision entry corresponding to a revisionnumber of information contained in the leaf node. Use of the leaf noderevision enables generating two or more similar indexes while savingeach revision of the two or more similar indexes. The node type field366 includes a node type, where the node type indicates whether the nodeis a leaf node or not a leaf node. The node type indicates that the nodeis a leaf node when the node is the leaf node.

The sibling node source name field 368 includes a sibling node sourcename entry (e.g., sibling node DSN address) corresponding to a storagelocation for a sibling when the leaf node has the sibling node as asibling. The sibling node is another leaf node when the leaf node hasthe sibling. The sibling node source name field 368 may include a nullentry when the leaf node does not have a sibling. The sibling minimumindex key field 370 includes a minimum index key associated with thesibling node when the leaf node has the sibling node as the sibling. Thesibling key type traits field 372 may include sibling key type traitscorresponding to the sibling node when the leaf node has the siblingnode as the sibling and when the sibling key type traits field 372 isutilized. Alternatively, index structure metadata may include key typetraits utilized globally for each leaf node of the index structure.

The data source name or data field 402 includes at least one of a datasource name entry (e.g., a DSN address) corresponding to a storagelocation of data and the data (e.g., a data object, one or more encodeddata slices of data). For example, a data 1 source name or data field402 of a data 1 information section 398 includes a DSN address sourcename of a first data object. As another example, the data 1 source nameor data field 402 of the data 1 information section includes the data 1data object. The data index key field 404 includes a data index keycorresponding to the data. For example, a data 1 index key field orderfor of the data 1 information section 398 includes a data 1 index key.The data key type traits field 406 may include data key type traitscorresponding to the data when the data key type traits field 406 isutilized. Alternatively, the index structure metadata may include keytype traits utilized globally for each data object associated with theindex structure.

FIG. 40D is a diagram illustrating another example of an index structureof an example index utilized to access data stored in at least one of adispersed storage network (DSN) memory and a distributed storage andtask network (DSTN) module. In the example, the index structure includesthree leaf nodes and three index nodes. Each of the three leaf nodes andthe three index nodes are individually encoded using a dispersed storageerror coding function to produce a set of corresponding node slices thatare stored in the DSTN module. The index structure provides an index forthree data objects stored in the DSTN module, where the data objectsstored in the DSTN module utilizing source names 76B, 8F6, and 92D, andglobal key type traits includes a comparing function to sort string typeindex keys alphabetically. The data stored at source name 76B isassociated with an index key of “a” as that data begins with a character“a”. The data stored at source name 8F6 is associated with an index keyof “d” as that data begins with a character “d”. The data stored atsource name 92D is associated with an index key of “j” as that databegins with a character “j”.

A leaf node stored at source name 5AB includes a node type indicating aleaf node, a sibling node source name pointing to a leaf node stored atsource name 52D, a sibling minimum index key of “d”, a data 1 sourcename of 76B, a data 1 index key of “a”, a data 2 direct data entry(e.g., b39d5ac9), and a data 2 index key of “b”. The leaf node stored atsource name 52D includes a node type indicating a leaf node, a siblingnode source name pointing to a leaf node stored at source name 539, asibling minimum index key of “j”, a data 1 source name of 8F6, and adata 1 index key of “d”. The leaf node stored at source name 539includes a node type indicating a leaf node, a null sibling node sourcename (e.g., since last leaf node of leaf node level), a null siblingminimum index key, a data 1 source name of 92D, and a data 1 index keyof “j”.

An index node stored at source name 4F7 includes a node type indicatingnot a leaf node (e.g., index node), a sibling node source name pointingto an index node stored at source name 42C, a sibling minimum index keyof “j”, a child 1 source name of 5AB, a child 1 minimum index key of“a”, a child 2 source name of 52D, and a child 2 minimum index key of“d”. The index node stored at source name 42C includes a node typeindicating not a leaf node (e.g., index node), a null sibling nodesource name (e.g., since last index node of an index node level), a nullsibling minimum index key, a child 1 source name of 539, and a child 1minimum index key of “j”. An index node (e.g., a root node) stored atsource name 2FD includes a node type indicating not a leaf node (e.g.,index node), a null sibling node source name (e.g., since root node), anull sibling minimum index key, a child 1 source name of 4F7, a child 1minimum index key of “a”, a child 2 source name of 42C, and a child 2minimum index key of “j”.

FIG. 40E is a diagram illustrating an example of a metadata objectstructure 410 that includes data object information 414 and segmentallocation table information 416. A metadata object is generated inaccordance with the metadata object structure 410 such that the metadataobject 410 describes a data object stored as one or more versions in adispersed storage and task network (DSTN). The metadata object is storedin the DSTN utilizing a metadata DSTN address 412. Each version of theone or more versions of the data is stored as two or more portions inthe DSTN. The data object information 414 includes common informationwith regards to the data object. The segment allocation tableinformation 416 includes information relating to the two or moreportions of each of the one or more versions.

In particular, the data object information 414 includes a data objectname field 418, a data index key field 420, and a total size of datafield 422. The data object name field 418 includes a data object nameassociated with the data. The data index key field 420 includes a dataindex key associated with the data object. The total size of data field422 includes a total size of data value associated with the data object.

The segment allocation table information 416 includes versioninformation 424 for each of the one or more versions of the data. Theversion information 424 includes portion information 426 for each of thetwo or more portions of the data. The portion information includes 426 aportion source name field 428, a portion size field 430, a portionnumber of segments field 432, and a segmentation method field 434. Theportion source name field 428 includes a starting source name of a firstsegment of a corresponding portion. The portion size field 430 includesa portion size of the portion (e.g., total number of bytes of theportion). The portion number of segments field 432 includes a number ofsegments for the portion. The segmentation method 434 field includes asegmentation method identifier (e.g., fixed size segmentation, variablesize segmentation, ramping size up segmentation, ramping size downsegmentation, etc.).

FIG. 40F is a flowchart illustrating an example of updating a cachedindex node. The method begins at step 440 where a processing module(e.g., of a distributed storage and task (DST) client module) determineswhether to delete a cached index node. The cached index node may bestored in a local memory associated with the DST client module inaddition to being stored as one or more sets of encoded index slices ina distributed storage and task network (DSTN) module. The cached indexnode may be cached upon one or more of retrieving the index node fromthe DSTN module and generating an updated version of the index node.

The determining may be based on one or more of a size of the index node,an age of the index node since last caching, an available storageresource level, a frequency level of index node retrieval, and a levelof the index node within an associated index. For example, processingmodule determines to delete the cached index node more often for lowestlevels of the index. As another example, the processing moduledetermines to delete the cached index node when the age of the indexnode since last storage is greater than a last storage threshold. As yetanother example, a processing module determines to delete the cachedindex node when the frequency level of index node retrieval is less thana retrieval threshold. The method branches to step 444 when theprocessing module determines to not delete the cached index node. Themethod continues to step 442 when the processing module determines todelete the cached index node. The method continues at step 442 where theprocessing module deletes the cached index node. The deleting includesdeleting the cached index node from a cache memory and resetting the ageof the index node since last storage.

The method continues at step 444 where the processing module sends a setof read if modified requests. The outputting includes generating the setof read if modified requests and outputting the set of read if modifiedrequests to the DSTN module. The set of read if modified requestsincludes at least one set of slice names associated with storage of theindex node in the DSTN module and a revision number associated with thecached index node. The method continues at step 446 where the processingmodule receives read if modified responses. Each read if modifiedresponse includes one or more of a slice name, one or more slicerevision numbers, and an updated index slice for each slice revisionnumber when the slice revision number of the one or more slice revisionnumbers is greater than the revision number of the cached index node.

When the read if modified responses include updated index slices, themethod continues at step 448) this where the processing module decodesat least a decode threshold number of the updated index slices using adispersed storage error coding function to produce an updated indexnode. The decoding includes selecting updated index slices correspondingto a latest revision of the one or more slice revision numbers. Themethod continues at step 450 where the processing module caches theupdated index node. For example, the processing module stores theupdated index node in the local memory. The caching may includegenerating and storing a timestamp associated with storage of theupdated index node.

FIG. 41 is a flowchart illustrating an example of updating an indexnode. The method begins at step 452 where a processing module (e.g., ofa distributed storage and task (DST) client module) receives a pluralityof index node update requests for an index node within an index nodeupdate time period. For example, the processing module receives 12 indexnode update requests for the index node within 100 ms when the indexnode update time period is established to be 100 ms. The methodcontinues at step 454 where the processing module queues the pluralityof index node update requests by time of arrival. For example, theprocessing module enters a first index node update request into a firstposition of a storage queue when the first index node update request wasreceived first, enters a second index node update request into a secondpossession of the storage queue when the second index node updaterequest was received second, etc.

When the index node update time period has elapsed, the method continuesat step 456 where the processing module retrieves the index node from adistributed storage and task network (DSTN) module. The retrievingincludes generating one or more sets of read slice requests thatincludes one or more sets of slice names corresponding to one or moresets of index slices, sending the one more sets of read slice requeststo the DSTN module, receiving one or more sets of at least a decodethreshold number of index slices, and decoding each of the one or moresets of at least the decode threshold number of index slices using adispersed storage error coding function to reproduce the index node.

For each index node update requests, the method continues at step 458where the processing module retrieves the request from the queue andperforms the update in order of time of arrival starting with the oldestrequest (e.g., first queued) to produce an updated index node. Theprocessing module sequentially performs each request of the plurality ofqueued index node update requests. The method continues at step 460where the processing module deletes the request from the queue uponperforming the update. The method continues at step 462 where theprocessing module stores the updated index node in the DSTN module. Thestoring includes encoding the updated index node using the dispersedstorage error coding function to produce one or more sets of updatedindex slices, generating one or more sets of write slice requests thatincludes the one or more sets of updated index slices and the one moresets of slice names corresponding to the one or more sets of indexslices, and outputting the one or more sets of write slice requests tothe DSTN module.

FIG. 42 is a flowchart illustrating an example of adjusting an indexnode update time period. The method begins at step 464 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule) determines a performance level of updating of an index node. Thedetermining includes one or more of detecting a frequency level ofupdate conflicts of the index node, detecting a frequency level ofupdate requests for the index node, and detecting an average time toupdate the index node. The method continues at step 466 where theprocessing module determines whether to modify an index node update timeperiod based on the performance level of the updating of the index node.The determining is based on comparing at least a portion of theperformance level of updating of the index node to one or moreperformance level thresholds. For example, processing module determinesto modify the index node update time period when the frequency level ofupdate conflicts of index node is greater than an update conflictfrequency threshold. The method loops back to step 464 when theprocessing module determines not to modify the index node update timeperiod. The method continues to step 468 when the processing moduledetermines to modify the index node update time period.

The method continues at step 468 where the processing module determineswhether to shorten the index node update time period. The determiningmay be based on the performance level of updating the index node and oneor more performance level thresholds. For example, the processing moduledetermines to shorten the next node update time period when thefrequency level of update conflicts of the index node is less than afrequency threshold and the frequency level of update requests for theindex node is less than an update threshold. As another example, theprocessing module determines to lengthen the index node update timeperiod when the average time to update the index node is greater than anupdate time threshold (e.g., using too much bandwidth). The methodbranches step 472 when the processing module determines to shorten theindex node update time period. The method continues to step 470 when theprocessing module determines to lengthen the index node update timeperiod.

The method continues at step 470 where the processing module lengthensthe index node update time period when the processing module determinesto lengthen the index node update time period. The processing module maylengthen the index update time period by adding a predetermined amountof time to the index node update time period to produce a modified indexnode update time period. The method continues at step 472 where theprocessing module shortens the index node update time period when theprocessing module determines to shorten the index node update timeperiod. The processing module may shorten the index update time periodby subtracting another predetermined amount of time from the index nodeupdate time period to produce the modified index node update timeperiod.

FIGS. 43A-B are schematic block diagrams of embodiments of a dispersedstorage network (DSN) that include a set of storage units, a network 24,and one or more devices (e.g., a first device 480, a second device 490).Each storage unit may be the distributed storage and task (DST)execution unit of FIG. 1. The network 24 may be the network 24 ofFIG. 1. Each device 480, 490 includes a DST client module 34 of FIG. 1.Each device 480, 490 may be the user device 12 of FIG. 1.

The DSN functions to store data from the first device 480 and the seconddevice 490 while avoiding a write conflict. The data may be revised fromtime to time producing revised data of an associated revision level. Thewrite conflict includes attempting to write a revision of the data thatassociated with a revision level that is not greater than all revisionlevels associated with currently stored recoverable revisions of thedata. For example, the write conflict is produced when the first devicewrites a first revision followed in time by the second device attemptingto write the first revision. As another example, the write conflict isproduced when the first device attempts to write a third revision of thedata when a fourth revision of the data is recoverable from the DSN.

The DST client module 34 encodes the data using a dispersed storageerror coding function to produce a plurality of sets of encoded dataslices. The DST client module 34 associates a common revision level witheach encoded data slice based on one or more of a revision levelassociated with a previously produced revision of the data, initiating alist command, receiving a list response, receiving a message fromanother device, and performing a lookup. When the data is revised, theDST client module 34 encodes the revised data to produce a plurality ofsets of revised encoded data slices. Next, the DST client module 34associates another common revision level with each revised encoded dataslice. As a specific example, the DST client module 34 associates arevision number of 4 as the revision level for each of the revisedencoded data slices when a revision number of 4 was the revision levelfor each of the encoded data slices associated with the data prior torevision.

In an example of writing the revised data to the set of storage unitswith reference to FIG. 43A, the DST client module 34 of the first device480 sends a set of write revision requests 482 to the storage units ofthe DSN. Each write revision request 1-n includes a slice name and arevision number corresponding to a revision level of a revised encodeddata slice to be stored in the DSN. The write revision request mayfurther include the revised encoded data slice of the respective revisedencoded data slices. Alternatively, the write revision request does notinclude the revision number when the storage units utilize a method togenerate a write revision response that doesn't require the revisionnumber as is discussed in more detail below. FIGS. 43C-D are timingdiagrams illustrating examples of timing of writing data from the DSTclient module 34 to DST EX unit 1. In particular, FIG. 43C illustratesan example when the DST client module 34 sends write revision request 1of the set of write revision request 482 to DST EX unit 1, where thewrite revision request includes a slice name, a revision number of 4,and a revised encoded data slice of revision 4. The DST EX unit 1temporarily stores (e.g., non-retrievable while temporarily stored) therevised encoded data slice of revision 4 and issues a write revisionresponse 1 to the DST client module 34. Having detected no conflictissue, the DST client module 34 issues a commit request 1 to the DST EXunit 1. The DST DX unit 1 non-temporarily stores the encoded data sliceof revision 4 (e.g., changing its status to retrievable fromnon-retrievable).

FIG. 43D illustrates another example when the DST client module 34 sendsthe write revision request 1 to the DST EX unit 1, where the writerevision request includes the slice name and the revision number of 4(e.g., no slice). The DST EX unit 1 issues the write revision response 1to the DST client module 34. Having detected no conflict issue, the DSTclient module 34 issues a write commit request 1 to the DST EX unit 1that includes the revised encoded data slice of revision 4. The DST DXunit 1 non-temporarily stores the encoded data slice of revision 4.

Returning to the discussion of FIGS. 43A-B, having received a writerevision request, each of the storage units locks the slice name for thewrite revision request. While the slice name is locked for the writerevision request, one of the storage units may receive a second writerevision request regarding the slice name from another device of the DSN(e.g., the second user device 490). When the second write revisionrequest is received, the storage unit sends a write error message to theother device (e.g., indicating a lock error status). The other devicemay try again when the lock is lifted upon completion of processing thewrite revision request from the first device 480.

The set of storage units further processes the set of write revisionrequests to generate a set of write revision responses 484 regarding apotential write conflict issue based on the revision number and send theset of write revision responses 484 to the first device 480. FIGS. 43E-Hare timing diagrams illustrating examples of timing of sending a writerevision response from DST EX unit 1 to the DST client module 34 inresponse to writing of data. As a specific example of FIG. 43E, the DSTclient module 34 issues a write revision request 1 to the DST EX unit 1that includes a slice name and a revision 4. The DST EX unit 1 generatesa write revision response 1 to include a list of revision numbers 1-3that corresponds to a number of revised encoded data slices having theslice name that the DST EX unit 1 is storing. As another specificexample of FIG. 43F, DST EX unit 1 generates the write revision response1 to include a most recent revision number 3 corresponding to a mostrecently stored one of the respective revised encoded data slices. Asyet another specific example of FIG. 43G, the DST EX unit 1 generatesthe write revision response 1 to include a favorable revision numberindication 4 and in FIG. 43H generates the write revision response 1 toinclude an unfavorable revision number indication 3. For instance, theDST EX unit 1 compares a most recent revision number 3 corresponding toa most recently stored one of the respective revised encoded data slicesto the revision number 4 of FIG. 43G or 3 of FIG. 43H. In the example ofFIG. 43G, when the most recent revision number 3 is less than therevision number 4, the DST EX unit 1 indicates the favorable revisionnumber indication 4. In the example of FIG. 43H, when the most recentrevision number 3 is greater than or equal to the revision number 3, theDST EX unit 1 indicates the unfavorable revision number indication 3.

Returning to the discussion of FIGS. 43A-B, the first device 480receives the write revision responses 484 from at least some of thestorage units to produce a set of received write revision responses. TheDST client module 34 interprets the set of received write revisionresponses to determine whether the write conflict issue exists. As aspecific example, when the storage unit generates the write revisionresponse to include the list of revisions, the first device 480interprets the lists of revision numbers of the set of received writerevision responses in view of the revision number by comparing a mostrecent revision number of the lists of revision numbers to the revisionnumber. When at least a decode threshold number of the lists of revisionnumbers compare favorably to the revision number, the first device 480indicates that the write conflict issue does not exist. As anotherspecific example, when the storage unit generates the write revisionresponse to include the most recent revision number, the first device480 interprets the most recent revision numbers of the set of receivedwrite revision responses in view of the revision number and when atleast a decode threshold number of the most recent revision numberscompare favorably (e.g. less than) to the revision number, the firstdevice 480 indicates that the write conflict issue does not exist. Asyet another specific example, when the storage unit generates the writerevision response to include the favorable or unfavorable revisionnumber indication, the first device 480 interprets the set of receivedwrite revision responses by indicating that the write conflict issuedoes not exist when at least a decode threshold number of favorablerevision number indications were received.

When the write conflict issue does not exist, the first device 480issues a set of next phase write requests 486 to the storage unitsregarding storing the respective revised encoded data slices. Forexample, next phase write request 1 includes the revised encoded dataslice of the respective revised encoded data slices when the revisedencoded data slice was not included in the write revision request 1. Asanother example, the next phase write request 1 includes a commitrequest 1 to instruct the DST EX unit 1 to non-temporarily store therevised encoded data slice that was included in the write revisionrequest 1.

FIG. 43B further illustrates an example when the write conflict issuedoes exist. In an example of operation, the second device 490, at timet, issues a set of write revision x requests 482 to the set of storageunits. DST EX units 1-n temporarily stores a set of revised encoded dataslices associated with revision x at approximately time t. The set ofstorage units issues write revision responses 1-n 484 with regards torevision x to the second device 490 indicating that a most recentrevision associated with the set of revised encoded data slices has arevision number of x−1 (e.g., no conflict since x−1<x). Having detectedno conflicts, the second device 490 issues a set of commit requests 1-nas next phase write requests 486 1-n to the set of storage units tonon-temporarily store the set of revised encoded data slices associatedwith revision x. Subsequent to completion of writing the set of revisedencoded data slices associated with revision x from the second device490, the first device 480, at time t+delta t, issues another set ofwrite revision x requests 482 to the set of storage units that includesanother set of revised encoded data slices associated with a revisionnumber of x. The set of storage units issues write revision responses484 with regards to revision x to the first device 480 indicating that amost recent revision associated with the set of revised encoded dataslices has a revision number of x (e.g., conflict since x not <x).Having detected the write conflict, the first device 480 issues a set ofrollback requests 488 regarding aborting storage of respective revisedencoded data slices (e.g., delete the other set of revised encoded dataslices from the first device 480).

FIGS. 43I-K are timing diagrams illustrating examples of writing data tothe set of storage units further illustrating the DST client module 34issuing the set of write revision requests 482 to the set of storageunits (e.g., DST EX units 1-3), the set of storage units issuing a setof write revision responses 1-3, and the DST client module 34 issuing aset of commit requests 492 (e.g., FIGS. 43I-J) when determining toproceed with storage of the set of revised encoded data slices oralternatively issuing a set of rollback requests 488 (e.g., FIG. 43K)when determining not to proceed with storage of the set of revisedencoded data slices. The FIGS. 43I-K further illustrate a storage systemwith a decode threshold is 2 and a set of storage units that includes 3storage units (e.g., pillar width of 3). The DST client module 34 issuesthe set of write revision requests 482 that includes the revised encodeddata slice of revision 4 to the set of storage units. Each of thestorage units issues a write revision response to the DST client module34.

In an example of proceeding with storage of the revised set of encodeddata slices when no conflict exists, FIG. 43I includes the storage unitsthat have previously stored different revisions of sets of revisedencoded data slices such that revision 2 is a most recently writtenrevision that is recoverable and each storage unit has a different mostrecent revision. The first storage unit issues a write revision response1 that includes a revision list of revisions 1-3. The second storageunit issues a write revision response 2 that includes a revision list ofrevisions 1-2. The third storage unit issues a write revision response 3that includes a revision list of revisions 1 and 3. Alternatively, anystorage unit may issue a corresponding write revision response thatincludes another format such as favorable/unfavorable and a most recentrevision number. Having received the set of write revision responses1-3, the DST client module 34 interprets the set of write revisionresponses to determine that no conflict exists and to proceed withissuing a set of commit requests 492 to the set of storage units. As aspecific example, the DST client module 34 interprets the set ofreceived revision lists to identify a revision 2 as a most recentrecoverable revision. Next, the DST client module 34 determines that noconflict exists since revision 4 is greater than revision 2. As anotherspecific example when the set of storage units issuesfavorable/unfavorable format write revision responses, the DST clientmodule 34 determines that no conflict exists since the decode thresholdnumber of the storage units sends favorable write revision responses(e.g., all storage units send favorable responses since 4>3 and 4>2). Asyet another specific example when the set of storage units issues themost recent revision format write revision responses, the DST clientmodule 34 determines that no conflict exists since the decode thresholdnumber of storage units (e.g., storage units 1 and 3) sends a mostrecent revision of 3 which is less than 4.

In an example of proceeding with storage of the revised set of encodeddata slices when some conflict exists, FIG. 43J includes the storageunits that have previously stored different revisions of sets of revisedencoded data slices such that revision 2 is a most recently writtenrevision that is recoverable and each storage unit has a different mostrecent revision (e.g., storage unit 1 has rev 4, unit 2 has rev 2, andunit 3 has rev 3). The first storage unit issues a write revisionresponse 1 that includes a revision list of revisions 1, 2, 4. Thesecond storage unit issues a write revision response 2 that includes arevision list of revisions 1-2. The third storage unit issues a writerevision response 3 that includes a revision list of revisions 1 and 3.Alternatively, any storage unit may issue a corresponding write revisionresponse that includes another format such as favorable/unfavorable anda most recent revision number. Having received the set of write revisionresponses 1-3, the DST client module 34 interprets the set of writerevision responses to determine that, while a conflict exists withstorage unit 1, to proceed with issuing a set of commit requests 492 tothe set of storage units. As a specific example, the DST client module34 interprets the set of received revision lists to identify a revision2 as a most recent recoverable revision. Next, the DST client module 34determines that no conflict exists since revision 4 is greater thanrevision 2. As another specific example when the set of storage unitsissues favorable/unfavorable format write revision responses, the DSTclient module 34 determines that no conflict exists since the decodethreshold number of the storage units sends favorable write revisionresponses (e.g., storage units 2-3 send favorable responses since 4>2and 4>3 while storage unit 1 sends an unfavorable response since 4not >4). As yet another specific example when the set of storage unitsissues the most recent revision format write revision responses, the DSTclient module 34 determines that, while a conflict exists with storageunit 1, proceed with the set of commit requests 492 since the decodethreshold number of storage units (e.g., storage units 2 and 3) sends amost recent revision of 2 and 3 which is less than 4.

In an example of not proceeding with storage of the revised set ofencoded data slices when some conflict exists, FIG. 43K includes thestorage units that have previously stored different revisions of sets ofrevised encoded data slices such that revision 5 is a most recentlywritten revision that is recoverable and the storage unit has a varietyof most recent revisions (e.g., storage unit 1 has rev 5, unit 2 has rev5, and unit 3 has rev 1). The first storage unit issues a write revisionresponse 1 that includes a revision list of revisions 1 and 5. Thesecond storage unit issues a write revision response 2 that includes arevision list of revisions 1 and 5. The third storage unit issues awrite revision response 3 that includes a revision list of revision 1.Alternatively, any storage unit may issue a corresponding write revisionresponse that includes another format such as favorable/unfavorable anda most recent revision number. Having received the set of write revisionresponses 1-3, the DST client module 34 interprets the set of writerevision responses to determine that one or more a conflicts exists andto issue a set of rollback requests 488 to the set of storage units(e.g., instead of commit requests). As a specific example, the DSTclient module 34 interprets the set of received revision lists toidentify a revision 5 as a most recent recoverable revision. Next, theDST client module 34 determines that the write conflict exists sincerevision 4 is not greater than revision 5. As another specific examplewhen the set of storage units issues favorable/unfavorable format writerevision responses, the DST client module 34 determines that conflictexists since a decode threshold number of the storage units is not sendfavorable write revision responses (e.g., storage units 1 and 2 sendunfavorable responses since 4 not >5 while storage unit 3 sends afavorable response since 4>1). As yet another specific example when theset of storage units issues the most recent revision format writerevision responses, the DST client module 34 determines that a conflictexists since the decode threshold number of storage units (e.g., storageunits 1 and 2) sends a most recent revision of 5 which is not less than4.

FIG. 43L is a flowchart illustrating an example of storing data. Themethod begins at step 500 where a first device of a dispersed storagenetwork (DSN) sends a set of write revision requests to storage units ofthe DSN. Each write revision request of the set of write revisionrequests includes a slice name and a revision number corresponding to arevision level of a revised encoded data slice to be stored in the DSN.The write revision request may further include the revised encoded dataslice of the respective revised encoded data slices. Alternatively, thewrite revision request does not include the revision number when thestorage units utilize a method to generate a write revision responsethat doesn't require the revision number (e.g., a revision list, a mostrevision) and the revised encoded data slice will be sent later alongwith a revision number.

The method continues at step 502 where one of the storage units locksthe slice name for a corresponding one of the set of write revisionrequests. While the slice name is locked for the corresponding one ofthe set of write revision requests, the method continues at step 504where the one of the storage units receives from a second device of theDSN, a second write revision request regarding the slice name (e.g.,same slice name). Alternatively, when not receiving the second writerevision request, the method branches to step 508. The method continuesat step 506 where the one of the storage units sends a write errormessage to the second device when the one of the storage units receivesthe second write revision request regarding the slice name.

The method continues at step 508 where the one of the storage unitsgenerates a write revision response regarding a potential write conflictissue based on the revision number. As a specific example, the one ofthe storage units generates the write revision response to include alist of revision numbers that corresponds to a number of revised encodeddata slices having the slice name that the one of the storage units isstoring. As another specific example, the one of the storage unitsgenerates the write revision response to include a most recent revisionnumber corresponding to a most recently stored one of the respectiverevised encoded data slices. As yet another specific example, the one ofthe storage units generates the write revision response to include afavorable or unfavorable revision number indication. For instance, theone of the storage units compares a most recent revision numbercorresponding to a most recently stored one of the respective revisedencoded data slices to the revision number. When the most recentrevision number is less than the revision number, the one of the storageunits indicates the favorable revision number indication. When the mostrecent revision number is greater than or equal to the revision number,the one of the storage units indicates the unfavorable revision numberindication.

The method continues at step 510 where the first device receives thewrite revision responses from at least some of the storage units toproduce a set of received write revision responses. The method continuesat step 512 where the first device interprets the set of received writerevision responses to determine whether a write conflict issue exists.As a specific example, when the storage unit generates the writerevision response to include the list of revision, the first deviceinterprets the lists of revision numbers of the set of received writerevision responses in view of the revision number by comparing a mostrecent revision number of the lists of revision numbers to the revisionnumber. When at least a decode threshold number of the lists of revisionnumbers compare favorably to the revision number, the first deviceindicates that the write conflict issue does not exist.

As another specific example, when the storage unit generates the writerevision response to include the most recent revision number, the firstdevice interprets the most recent revision numbers of the set ofreceived write revision responses in view of the revision number andwhen at least a decode threshold number of the most recent revisionnumbers compare favorably (e.g., less than) to the revision number, thefirst device indicates that the write conflict issue does not exist. Asyet another specific example, when the storage unit generates the writerevision response to include the favorable or unfavorable revisionnumber indication, the first device interprets the set of received writerevision responses by indicating that the write conflict issue does notexist when at least a decode threshold number of favorable revisionnumber indications were received.

When the write conflict issue exists, the method continues at step 514where the first device issues a set of write roll back requests to thestorage units regarding aborting storage of respective revised encodeddata slices. As a specific example, the first device generates arollback request to include one or more of a corresponding slice name,the revision number, and a transaction number associated with the set ofwrite revision requests. When the write conflict issue does not exist,the method continues at step 516 where the first device issues a set ofnext phase write requests to the storage units regarding storing therespective revised encoded data slices. As a specific example, the firstdevice generates a next phase write request to include a write commitrequest including one or more of the corresponding slice name, therevision number, and the transaction number associated with the set ofwrite revision requests.

FIGS. 44A-B are schematic block diagrams of more embodiments of adispersed storage network (DSN) that include a first device 520, asecond device 526, a network 24, and a set of distributed storage andtask (DST) execution units 1-n. The first device 520 may be the userdevice 12 of FIG. 1. A second device 526 may be the DST processing unit16 of FIG. 1. The first and second devices 520, 526, include the DSTclient module 34 of FIG. 1. Each DST execution unit of the set of DSTexecution units 1-n may be the DST execution unit 36 of FIG. 1. Each DSTexecution unit includes the processing module 84 of FIG. 3.

Data is segmented to produce a plurality of data segments. A datasegment of the plurality of data segments is dispersed storage errorencoded to produce a set of encoded data slices. A plurality of sets ofencoded data slices is stored in the set of DST execution units 1-n.Each of the DST execution units stores a different portion of the data.The different portion of the data corresponds to one or more encodeddata slices of one or more sets of encoded data slices.

Each DST client module 34 stores a copy of the data by caching in localmemory (e.g., of the DST client module 34, of the first and seconddevices). One or more local memory revision numbers correspond to thedifferent portions of the data that are cached in the local memory. Forexample, the DST client module 34 of the first device 520 stores a setof portions A 1-n (e.g. corresponding to data A) that correspond to asecond revision of data A. As a specific example of determining the oneor more local memory revision numbers, the DST client module 34determines a common revision number (e.g., rev 2) for the differentportions of the data as the one or more local memory revision numbers.As another specific example, the DST client module 34 determines a localrevision number (e.g., rev 2) for each of the different portions of thedata as the one or more local memory revision numbers.

From time to time, each DST client module 34 updates storage of the copyof the data when a newer revision of the data is stored in the set ofDST execution units 1-n. FIG. 44A illustrates an example of the updatingwhen the copy of the data does not require the updating and FIG. 44Billustrates another example of the updating when the copy of the datarequires the updating. When the copy of data is cached in the localmemory of the first device 520, the DST client module 34 sends, via thenetwork 24, read-if-revised requests 522 to the set of DST executionunits 1-n as a set of read if revised requests 1-n. The read-if-revisedrequests 522 includes a name of the data (e.g., a DSN address, a slicename) and the one or more local memory revision numbers corresponding tothe different portions of the data that are cached in the local memory.As a specific example, the DST client module 34 sends theread-if-revised requests 522 as a query to determine whether the datacached in the local memory is outdated (e.g., based on detecting apotentially outdated encoded data slice). As another specific example,the first device sends the read-if-revised requests 522 as a readrequest to read the data from the set of DST execution units (e.g., anactive process requires the data within the DST client module 34). Asyet another specific example, the DST client module 34 sends theread-if-revised requests in response to a scheduled task (e.g., checkdata synchronization every two minutes).

Having received a read if modified request 1, DST execution unit 1determines whether a revision number of one of the different portions ofthe data stored by the DST execution unit 1 is a more recent revisionnumber than the one or more local memory revision numbers of the read ifmodified request 1 (e.g., more recent when revision number greater thanrevision number of the request). When the revision number of the one ofthe different portions of the data stored by the DST execution unit 1 isnot the more recent revision number than the one or more local memoryrevision numbers, the DST execution unit 1 sends a read response 1 thatincludes an indication that, with respect to the one of the differentportions of the data, the data cached in the local memory by the DSTclient module 34 of the first device 520 is a current revision level ofthe data (e.g., the revision number of the DST execution unit 1 is equalto or less than the one or more local memory revision numbers).

FIGS. 44C-E are timing diagrams illustrating examples of timing ofreading data and providing read responses that includes the DST clientmodule 34 and the DST execution unit 1. In particular, FIG. 44Cillustrates an example of DST execution unit 1 sending the read response1 that includes the indication that the data cached in the local memoryby the DST client module 34 is the current revision level of the data.As a specific example, the DST execution unit 1 sends the read response1 to include a list of revision numbers (e.g., rev 1, 2 for data name A)corresponding to the one of the different portions of the data. Asanother specific example, the DST execution unit 1 sends the readresponse 1 to include the more recent revision number (e.g., revision2). As yet another specific example, the DST execution unit 1 sends theread response 1 to include a favorable indication (e.g., favorable toindicate that the one or more local memory revision numbers are notoutdated).

FIGS. 44F-H are timing diagrams illustrating examples of reading dataand providing read responses that includes the DST client module 34 anda set of DST execution units 1-3 when a pillar width is three and adecode threshold is 2. In particular, FIG. 44F illustrates the examplewhen the data cached in the local memory by the DST client module 34 isthe current revision level of the data. For instance, the DST clientmodule 34 stores portions of data A corresponding to a third revisionlevel and each of the DST execution units stores portions of data Acorresponding to revisions 1-3. The DST client module 34 sends a read ifmodified requests to the set of DST execution units. For the example,the DST client module 34 sends the read if modified request to DSTexecution unit 1 with regards to a first portion of data A of revision3. Each of the DST execution units sends a read response that includesan indication that the data cached in the local memory is the currentrevision level of the data. For example, DST execution unit 2 sends aread response that includes, for a second portion of data A, a revisionlist of revisions 1-3. Accordingly, the portions of data A cached theDST client module 34 do not require updating.

Returning to the discussion of FIG. 44A, the DST client module 34 of thefirst device 520 receives read responses 524 from the set of DSTexecution units 1-n as read responses 1-n (e.g., confirming that thedata cached in local memory is a current revision level of the data).When the revision number of one of the different portions of the datastored by the DST execution unit 1 is less than the one or more localmemory revision numbers, the DST execution unit 1 initiates rebuildingof the one of the different portions of the data. For example, the DSTexecution unit 1 performs the rebuilding. As another example, the DSTexecution unit 1 issues a rebuilding request to a rebuilding entity ofthe DSN, where the rebuilding request includes identity of the one ofthe different portions of the data.

The DST execution unit 1 determines whether, based on the name of thedata received in the read if revised request 1, a new portion of thedata is stored by the DST execution unit 1 (e.g., additional encodeddata slices of additional data segments). When the DST execution unit 1determines that the new portion of the data is stored by the DSTexecution unit 1, the DST execution unit 1 sends the read response 1 tofurther include the new portion of the data (e.g., the additionalencoded data slices). The DST client module 34 caches the new portion ofthe data in the local memory.

FIG. 44B illustrates another example of the updating of the storage ofthe copy of the data when the newer revision of the data is stored inthe set of DST execution units 1-n. The second device 526 creates arevised version 3 of the data A and, at time t, issues a set of writerequests 528 to the set of DST execution units 1-n as write requests1-n. The set of DST execution units 1-n, at time t, store revisions 2-3of the portions of data A. first device 520 stores the copy of data Awith revision level 2 prior to time t. Subsequent to time t, the DSTclient module 34 of the first device 520 sends, at time t+delta t, readif revised requests 522 to the set of DST execution units 1-n withregards to portions 1-n of data A stored in the local memory with therevision level of 2. The set of DST execution units 1-n receives read ifrevised requests 1-n regarding revision 2 (e.g., the one or more localmemory revision numbers).

When the revision number of the one of the different portions of thedata stored by the DST execution unit 1 is the more recent revisionnumber than the one or more local memory revision numbers, the DSTexecution unit 1 sends sending a read response 1 that includes the oneof the different portions of the data to the to the DST client module 34of the first device 520 (e.g., the revision number of the DST executionunit 1 is greater than the one or more local memory revision numbers).The read response further includes at least one of the list of revisionnumbers (e.g., rev 2-3) corresponding to the one of the differentportions of the data, the more recent revision number (e.g., 3), and anunfavorable indication (e.g., unfavorable to indicate that the one ormore local memory revision numbers of rev 2 are outdated). The DSTclient module 34 of the first device 520 updates caching of the data inthe local memory to include the one of the different portions of thedata (e.g., the first device stores a newer revision 3 from the set ofDST execution units 1-n).

FIGS. 44D-E illustrate examples of timing of reading data and providingthe read responses when the one of the different portions of the datastored by the DST execution unit 1 is the more recent revision numberthan the one or more local memory revision numbers (e.g., rev 2). Inparticular, FIG. 44D illustrates an example of DST execution unit 1sending the read response 1 that includes the indication that the datacached in the local memory by the DST client module 34 is not thecurrent revision level of the data and the one of the different portions(e.g., revision 3 of portion 1 of data A). As a specific example, theDST execution unit 1 sends the read response 1 to include a list ofrevision numbers (e.g., rev 1, 2, 3 for data name A) corresponding tothe one of the different portions of the data. As another specificexample, the DST execution unit 1 sends the read response 1 to includethe more recent revision number (e.g., revision 3). As yet anotherspecific example, the DST execution unit 1 sends the read response 1 toinclude an unfavorable indication (e.g., unfavorable to indicate thatthe one or more local memory revision numbers are outdated since 3>2).

FIG. 44D-E illustrates examples of DST execution unit 1 sending the readresponse 1 that includes the indication that the data cached in thelocal memory by the DST client module 34 is not the current revisionlevel of the data and the one of the different portions (e.g., revisions3 and 4 of portion 1 of data A). As a specific example, the DSTexecution unit 1 sends the read response 1 to include a list of revisionnumbers (e.g., rev 2, 3, 4 for data name A) corresponding to the one ofthe different portions of the data. As another specific example, the DSTexecution unit 1 sends the read response 1 to include the more recentrevision number (e.g., revision 4). As yet another specific example, theDST execution unit 1 sends the read response 1 to include an unfavorableindication (e.g., unfavorable to indicate that the one or more localmemory revision numbers are outdated since 4>2).

FIGS. 44G-H illustrates examples of DST execution units 1-3 sending theread responses 1-3 that includes the indication that the data cached inlocal memory by the DST client module 34 is not the current revisionlevel of the data and the one or more different portions. The DST clientmodule 34 stores portions of data A comment where a first and thirdportions corresponds to a revision level 3 and a second portioncorresponds to a revision level 2. In particular, FIG. 44G illustratesan example when each of the DST execution units stores portions of dataA corresponding to revisions 1-3. The DST client module 34 sends read ifmodified requests to DST execution units 1 and 3 with regards torevision 3 and another read if modified request to DST execution unit 2with regards to revision 2. The DST execution units 1 and 3 sends readresponses that includes an indication that the data cached in the localmemory is the current revision level of the data. For example, the DSTexecution units 1 and 3 sends the read response that includes a revisionlist of revisions 1-3. Accordingly, the first and third portions of dataA cached by the DST client module 34 do not require updating. The DSTexecution unit 2 sends a read response that includes the third revisionof the second portion of data A and an indication that the data cachedin the local memory is not the current revision level of the data. Forexample, the DST execution unit 2 sends the read response that includesthe third revision of the second portion of data A and the revision listof revisions 1-3. Accordingly, the DST client module 34 updates thesecond portion of data A with the third revision.

FIG. 44H illustrates another example when each of the DST executionunits stores portions of data A corresponding to revisions 2-4. The DSTclient module 34 sends read if modified requests to DST execution units1 and 3 with regards to revision 3 and another read if modified requestto DST execution unit 2 with regards to revision 2. The DST executionunits 1 and 3 sends read responses that includes a fourth revision ofthe first and third portions of data A and an indication that the datacached in the local memory is not the current revision level of thedata. The DST execution unit 2 sends a read response that includes thethird and fourth revisions of the second portion of data A and anindication that the data cached in the local memory is not the currentrevision level of the data. Accordingly, the DST client module 34updates each portion 1-3 of data A with the fourth revisions.

FIG. 44I is a flowchart illustrating an example of reading data. When acopy of data is cached in local memory of a first device of adistributed storage network (DSN), the method begins at step 530 wherethe first device sends read-if-revised requests to storage units of theDSN. Each of the storage units stores a different portion of the data.The read-if-revised requests includes a name of the data (e.g., a DSNaddress, a slice name) and one or more local memory revision numberscorresponding to the different portions of the data that are cached inthe local memory. The data is segmented to produce a plurality of datasegments. A data segment of the plurality of data segments is dispersedstorage error encoded to produce a set of encoded data slices. Aplurality of sets of encoded data slices is stored in the storage units.The different portion of the data corresponds to one or more encodeddata slices of one or more sets of encoded data slices. As an example ofsending the read-if-revised requests, the first device sends theread-if-revised requests as a query to determine whether the data cachedin the local memory is outdated. As another example, the first devicesends the read-if-revised requests as a read request to read the datafrom the storage units. As yet another example, the first device sendsthe read-if-revised requests in response to a scheduled task. As anexample of determining the one or more local memory revision numbers,the first device determines a common revision number for the differentportions of the data as the one or more local memory revision numbers.As another example, the first device determines a local revision numberfor each of the different portions of the data as the one or more localmemory revision numbers.

The method continues at step 532 where a storage unit of the storageunits determines whether a revision number of one of the differentportions of the data stored by the storage unit is a more recentrevision number than the one or more local memory revision numbers. Themethod branches to step 538 when the storage unit determines that therevision number of the one of the different portions of the data storedby the storage unit is not the more recent revision than the one or morelocal memory revision numbers. The method continues to step 534 when thestorage unit determines that the revision number of the one of thedifferent portions of the data stored by the storage unit is the morerecent revision than that one or more local memory revision numbers.

When the revision number of the one of the different portions of thedata stored by the storage unit is the more recent revision number thanthe one or more local memory revision numbers, the method continues atstep 534 where the storage unit sends sending a read response thatincludes the one of the different portions of the data to the firstdevice (e.g., the revision number of the storage unit is greater thanthe one or more local memory revision numbers). The read responseincludes at least one of a list of revision numbers corresponding to theone of the different portions of the data, the more recent revisionnumber, and an unfavorable indication (e.g., unfavorable to indicatethat the one or more local memory revision numbers are outdated). Themethod continues at step 536 where the first device updates caching ofthe data in the local memory to include the one of the differentportions of the data (e.g., the first device stores a newer revisionfrom the storage unit). The method branches to step 542.

When the revision number of the one of the different portions of thedata stored by the storage unit is not the more recent revision numberthan the one or more local memory revision numbers, the method continuesat step 538 where the storage unit sends a read response that includesan indication that (e.g., list of revision numbers, a most recentrevision number, a favorable indication), with respect to the one of thedifferent portions of the data, the data cached in the local memory is acurrent revision level of the data (e.g., the revision number of thestorage unit is equal to or less than the one or more local memoryrevision numbers). When the revision number of one of the differentportions of the data stored by the storage unit is less than the one ormore local memory revision numbers, the method continues at step 540where the storage unit initiates rebuilding of the one of the differentportions of the data.

The method continues at step 542 where the storage unit determines,based on the name of the data, that a new portion of the data is storedby the storage unit (e.g., additional encoded data slices of additionaldata segments). The method continues at step 544 where the storage unitsends the read response to further include the new portion of the data(e.g., the additional encoded data slices).

FIG. 45A is a schematic block diagram of another embodiment of adistributed computing system that includes a plurality of user devices12, a plurality of distributed storage and task (DST) processing units16, and the distributed storage and task network (DSTN) managing unit 18of a DSTN of FIG. 1. The system functions to authenticate the pluralityof user devices 12 and to authorize DSTN access requests 560 from theplurality of user devices 12.

In an example of operation to authenticate a user device 12, the userdevice 12 generates an authentication request 550. The authenticationrequest 550 includes one or more of a user name associated with the userdevice 12 and a user device password associated with the user device 12.The user device 12 sends the authentication request 550 to a DSTprocessing unit 16. The DST processing unit 16 generates a proxiedauthentication request 552 based on the authentication request 550. Theproxied authentication request 552 includes one or more of the username,the user device password, a DST identifier (ID) associated with the DSTprocessing unit 16, a DST processing unit public key of a public-privatekey pair, and a signed certificate (e.g., signed by a certificateauthority of the DSTN). The DST processing unit 16 sends the proxiedauthentication request five and 52 to the DSTN managing unit 18.

The DSTN managing unit 18 authenticates the proxied authenticationrequest 552 by a series of steps. A first step includes comparing theusername and DST ID to an entry of allowed user device/DST processingunit principal associations maintained by an access control list (ACL).The principal associations identify two or more principals that arerequired to operate together. When the comparison is favorable (e.g., anallowed pairing or association), a second step includes verifying thesigned certificate utilizing the DST processing unit public key inaccordance with a certificate verification approach. For example, theDSTN managing unit 18 decrypts a signature of the signed certificateutilizing at least one of the DST processing unit public key and apublic key associated with the certificate authority to produce adecrypted signature. The DSTN managing unit 18 verifies the signedcertificate as valid when the decrypted signature compares favorably(e.g., substantially the same) to a result produced by performing adeterministic function (e.g., a hashing function) on the signedcertificate. Other verification procedures may be utilized. The DSTNmanaging unit 18 indicates that the proxied authentication request 552is authenticated when the comparison is favorable.

When the DSTN managing unit 18 indicates that the proxied authenticationrequest 552 is authenticated, the DSTN managing unit 18 generates aproxied authentication response 554 that includes an indication that theauthentication request 552 is favorably authenticated. When the DSTNmanaging unit 18 indicates that the proxied authentication request 552is not authenticated, the DSTN managing unit 18 generates a proxiedauthentication response 554 that includes one or more of an indicationthat the authentication request 550 is not authenticated and allowableprincipal associations that include the user device 12. The DSTNmanaging unit 18 sends the proxied authentication response 554 to theDST processing unit 16. The DST processing unit 16 generates anauthentication response 558 based on the proxied authentication response554. The authentication response 558 includes one of an authenticatedindicator and a not authenticated indicator. When the authenticationresponse 558 includes the not authenticated indicator, theauthentication response 558 further includes the allowable principalassociations. The user device 12 may access a different DST processingunits 16 to achieve a favorable allowable principal association for asubsequent authentication request 550 based on the authenticationresponse 558.

In an example of operation to authorize the user device 12, the DSTNmanaging unit 18 distributes an access control list 556 to the pluralityof DST processing units 16 for utilization during an access requestsequence. The access control list 556 includes a plurality of entries.An entry of the plurality of entries includes a vault ID, an accesstype, principal IDs, and a principal threshold number. One or more userdevices 12 of the plurality of user devices 12 each generates the accessrequest 560 that includes an access type and a user device ID. The userdevice 12 sends the access request 560 to an associated DST processingunit 16. The DST processing unit 16 authorizes the access request 560 bya series of steps. A first step includes verifying that the user device12 is favorably authenticated. A second step includes comparing userdevice ID and access type of the access request 560 to the accesscontrol list 556 to determine whether the access request 560 is allowed.For example, the DST processing unit 16 allows the access request 560when the access type and the user device ID compares favorably to anentry of the access control list 556 that includes the access type andthe user device ID. A third step includes determining whether a numberof the user device IDs compares favorably (e.g., greater than) to theprincipal threshold number when more than one user device is issuingassociated access request 560. For example, the DST processing units 16indicates that the one or more access requests are authorized when thenumber of user device IDs (e.g., received and compare favorably to theACL entry) is greater than or equal to the principal threshold number.

The DST processing unit 16 generates one or more access responses 562 toinclude results of authorization of the one or more access requests 560.An access response 562 includes one of an authorized indicator and a notauthorized indicator. When the access response includes the notauthorized indicator, the access response 562 may further include theprincipal IDs and the principal threshold number. The one more userdevices 12 may coordinate generation of a different one or more accessrequests 560 to achieve a favorable authorized indicator for asubsequent access request scenario. The method to authorize the one moreaccess requests is described in greater detail with reference to FIG.45B.

FIG. 45B is a flowchart illustrating an example of authenticating anaccess request. The method begins at step 564 where a processing module(e.g., of a distributed storage and task (DST) processing unit) receivesan access request from a user device. The method continues at step 566where the processing module verifies authentication of the user device.For example, the processing module checks a recently authenticated listto verify that the user device has recently been favorablyauthenticated.

When the authentication is favorably verified, the method continues atstep 568 where the processing module determines whether similar accessrequests from a principal threshold number of the devices have beenreceived. The method branches to step 574 when similar access requestsfrom the principal threshold number of user devices have been received.The method continues to step 570 when similar access requests from theprincipal threshold number of user devices have not been received. Themethod continues at step 570 where the processing module generates anaccess response to include denial information. The denial informationincludes one or more of a reason denied code, identifiers of principalsinvolved, identifiers of allowed principals not involved, and theprincipal threshold number. The method continues at step 572 where theprocessing module outputs the access response to the user device.Alternatively, or in addition to, the processing module sends the accessresponse to other associated principals (e.g., other user devices).

The method continues at step 574 where the processing module facilitatesexecution of the access request when the similar access requests fromthe principal threshold number of user devices have been received. Thefacilitating includes at least one of executing a read request, a writerequest, a list request, etc. The method continues at step 576 where theprocessing module generates an access response to include a result ofexecution of the access request. For example, the processing modulegenerates the access response to include an encoded data slice when theaccess request includes a request to read the encoded data slice. Asanother example, the processing module generates the access response toinclude a write confirmation indicator when the access request includesa request to write the encoded data slice. The method continues at step578 where the processing module outputs the access response to the userdevice. Alternatively, or in addition to, the processing module outputsthe access response to other requesting principals.

FIG. 46A is a schematic block diagram of another embodiment of adistributed computing system that includes a distributed storage andtask (DST) client module 34 and a plurality of DST execution units 36 ofFIG. 1. In an example of operation, the system stores data segments assets of encoded data slices 1-6 in the plurality of DST execution units36. The DST client module 34 encodes each data segment using a dispersedstorage error coding function to produce a set of encoded data slices inaccordance with dispersal parameters. The dispersal parameters includesa pillar width a decode threshold. The DST client module 34 maydetermine the dispersal parameters based on storage conditions. Thestorage conditions includes one or more of current dispersal parameters,a reliability goal, an availability goal, a performance goal, an actualreliability level, an actual availability level, an actual performancegoal, and estimates of one or more of reliability, availability, andperformance. For example, the DST client module 34 determines thedispersal parameters to include a pillar width of six when six DSTexecution units 36 of the plurality of DST execution units 36 areassociated with favorable availability. As another example, the DSTclient module 34 determines the dispersal parameters to include a decodethreshold of four in accordance with an estimated reliability level whenthe pillar width is six.

The determining of the dispersal parameters may be dynamic as a functionof changes of the storage conditions. For example, the DST client module34 determines the dispersal parameters to include pillar width of fivewhen one of the previously available six DST execution units 36 becomesunavailable. As another example, the DST client module 34 determines toupdate the decode threshold to three in accordance with an estimatedreliability level when the pillar width is five. In addition, the DSTclient module 34 may retrieve at least one previously stored datasegment utilizing a previous set of dispersal parameters to reproducethe data segment for re-encoding utilizing the dispersal parameters forre-storage in an updated pillar width number of the plurality of DSTexecution units 36. The method of operation to store data utilizingusing adaptively determined dispersal parameters is discussed in greaterdetail with reference to FIG. 46B.

FIG. 46B is a flowchart illustrating another example of storing data.The method begins at step 580 where a processing module (e.g., of adistributed storage and task (DST) client module) receives a writerequest to store data in a distributed storage and task network (DSTN)module. The method continues at step 582 where the processing moduleidentifies a DST execution unit storage set associated with the data(e.g., identify a vault based on a identifier of a requesting entity bya registry lookup, identify the storage set based on the vault ID by alookup by a registry lookup). The method continues at step 584 where theprocessing module determines an availability level of the DST executionunit storage set. The availability level includes at least one of howmany DST execution units of the DST execution unit storage set are notoperational and which DST execution units of the DST execution unitsstorage set are operational. The determining may be based on one or moreof initiating a test, initiating a query, receiving a response, andperforming a lookup.

The method continues at step 586 where the processing module determineswhether to modify dispersal parameters associated with the DST executionunit storage set based on storage conditions including the availabilitylevel of the DST execution unit storage set. For example, the processingmodule determines to modify dispersal parameters when the availabilitylevel of the DST execution unit storage set is less than an availabilitylevel threshold. When modifying the dispersal parameters, the methodcontinues at step 588 where the processing module determines modifieddispersal parameters based on the dispersal parameters and the storageconditions including the availability level of the DST execution unitstorage set. For example, the processing module determines modifieddispersal parameters to include a pillar width of six when the dispersalparameters includes a pillar width of five and the availability level ofthe DST execution unit storage set indicates that six DST executionunits are now available. As another example, the processing moduledetermines the modified dispersal parameters to include a decodethreshold of four when the dispersal parameters includes a decodethreshold of three and an estimated reliability level of the DSTexecution unit storage set that includes six DST execution unitscompares favorably with a reliability level threshold when utilizing thedecode threshold four.

The method continues at step 590 where the processing module encodes thedata using a dispersed storage error coding function in accordance withthe modified dispersal parameters to produce a plurality of sets ofencoded data slices. The method continues at step 592 where theprocessing module outputs the plurality of sets of encoded data slicesto at least some DST execution units (e.g., to available units) of theDST execution unit storage set. The method continues at step 594 wherethe processing module recovers other data from the DST execution unitstorage set utilizing the dispersal parameters. The recovering includesretrieving slices from available DST execution units and decoding theretrieved slices using the dispersal parameters to reproduce the otherdata. The method continues at step 596 where the processing moduleencodes the other data using the dispersed storage error coding functionin accordance with the modified dispersal parameters to produce aplurality of sets of modified encoded data slices. The method continuesat step 598 where the processing module outputs the plurality of sets ofmodified encoded data slices to at least some DST execution units (e.g.,available units) of the DST execution unit storage set.

FIG. 47 is a flowchart illustrating an example of rebuilding data. Themethod begins at step 600 where a processing module (e.g., of adistributed storage and task (DST) client module) detects that less thana pillar width number of encoded data slices of a set of encoded dataslices of a common revision are retrievable from a distributed storageand task network (DSTN) module. The detecting includes at least one ofreceiving a message, invoking a list query, and comparing queryresponses. The method continues at step 602 where the processing moduleidentifies dispersal parameters associated with a set of encoded dataslices. The identifying includes at least one of performing a registrylookup, reading at least one encoded data slice of the set of encodeddata slices, and extracting the dispersal parameters from the at leastone encoded data slice.

When the less then the pillar width number of encoded data slicesincludes at least a decode threshold number of encoded data slices, themethod continues at step 604 where the processing module retrieves theat least the decode threshold number of encoded data slices. Theretrieving includes generating at least a decode threshold number ofread slice requests for any available decode threshold number of encodeddata slices of the set of encoded data slices, outputting the at leastthe decode threshold number of reads slice requests to the DSTN module,and receiving the least the decode threshold number of encoded dataslices.

The method continues at step 606 where the processing module decodes thedecode threshold number of encoded data slices using a dispersed storageerror coding function in accordance with the dispersal parameters toreproduce a data segment. The method continues at step 608 where theprocessing module determines whether to rebuild one or more encoded dataslices such that when combined with the less than the pillar widthnumber of encoded data slices reforms a full pillar width number ofencoded data slices. The determining may be based on one or more of thedispersal parameters, a memory availability indicator, a reliabilitygoal, a performance goal, a request, a lookup, and a predetermination.For example, the processing module determines to rebuild the one or moreencoded data slices when a reliability goal indicates to always providea full pillar width number of encoded data slices. The method branchesto step 614 when the processing module determines not to rebuild the oneor more encoded data slices. The method continues to step 610 when theprocessing module determines to rebuild the one or more encoded dataslices.

The method continues at step 610 where the processing module encodes thedata segment using the dispersed storage error coding function inaccordance with the dispersal parameters to produce the one or moreencoded data slices. The method continues at step 612 where theprocessing module facilitates storing the one or more encoded dataslices in the DSTN module associated with the common revision. Thefacilitating includes, for each slice of the one more encoded dataslices, generating a write slice request that includes the encoded dataslice and a revision number of the common revision.

The method continues at step 614 where the processing module encodes thedata segment using the dispersed storage or coding function inaccordance with the dispersal parameters to reproduce the set of encodeddata slices (e.g., full pillar width set) when the processing moduledetermines not to rebuild the one or more encoded data slices. Themethod continues at step 616 where the processing module facilitatesstoring the reproduced set of encoded data slices in the DSTN moduleassociated with a new revision. The facilitating includes generating aset of write slice requests that includes the set of encoded data slicesand a new revision number.

FIG. 48A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask (DST) client module 34, a plurality of the DST processing unit 16,and the distributed storage and task network (DSTN) module 22 of FIG. 1.The system functions to store data 618 in the DSTN module 22. The DSTclient module 34 encodes the data 618 (e.g., a data segment) using adispersed storage error coding function utilizing first level dispersalparameters to produce a first level set of encoded data slices 1-N. Thefirst level dispersal parameters includes a pillar width N and a decodethreshold K. The plurality of DST processing unit 16 includes a set of NDST processing units 16.

The DST client module 34 sends the first level set of encoded dataslices 1-N to the set of DST processing unit 16. Each DST processingunit 16 encodes a corresponding first level encoded data slice using thedispersed storage error coding function utilizing second level dispersalparameters to produce a corresponding second level set of encoded dataslices 1-n. The second level dispersal parameters includes a pillarwidth n and a decode threshold k. For example, a first DST processingunit 16 of the set of DST processing units 16 encodes data slice 1 ofthe set of encoded data slices 1-N using the dispersed storage errorcoding function utilizing the second level dispersal parameters toproduce a second level set of encoded data slices 1_(—)1 through 1_n.Next, the DST processing unit 16 outputs the corresponding second levelset of encoded data slices 1-n to the DSTN module 22 for storagetherein.

The DST processing unit 16 receives a confirmation from the DSTN module22 that at least a second level dispersal parameters write thresholdnumber of the second level set of encoded data slices 1-n have beensuccessfully stored in the DSTN module 22. When the DST processing unit16 receives the confirmation, the DST processing unit 16 generates aslice storage confirmation message and outputs the slice storageconfirmation message to the DST client module 34. The DST client module34 receives slice storage confirmation messages from at least some ofthe set of DST processing unit 16. When a first level dispersalparameters write threshold number of slice storage confirmation messageshave been received by the DST client module 34, the DST client module 34generates and outputs a cancellation message (e.g., rollback, delete) toany remaining DST processing unit 16 that have not output a sliceconfirmation message to the DST client module 34. The DST client modulecreates a directory entry for the data segment that includes object IDsassigned to each encoded data slice of the set of encoded data slices1-N corresponding to the first level dispersal parameters writethreshold number of slice storage confirmation messages.

The system may also function to retrieve the data segment from the DSTNmodule 22. When receiving a read request for the data segment, the DSTclient module 34 accesses the directory entry for the data segment toobtain the object IDs for each encoded data slice corresponding to thefirst level dispersal parameters write threshold number of slice storageconfirmation messages. Next, the DST client module generates and outputsretrieval requests for each encoded data slice corresponding to thefirst level dispersal parameters write threshold number of slice storageconfirmation messages to corresponding DST processing units 16. Each DSTprocessing unit 16 of the corresponding DST processing units 16retrieves at least a second level dispersal parameter decode thresholdnumber of encoded data slices from the DSTN module 22, decodes theretrieved encoded data slices to reproduce a corresponding slice, andoutputs a corresponding encoded data slice to the DST client module 34.The DST client module 34 decodes at least a first level dispersalparameter decode threshold number of received corresponding encoded dataslices to reproduce the data segment. The method of operation to storethe data segment is discussed in greater detail with reference to FIG.48B.

FIG. 48B is a flowchart illustrating another example of storing data.The method begins at step 620 where a processing module (e.g., of adistributed storage and task (DST) client module) receives a request tostore data. The request may include one or more of a data object and adata identifier (ID) associated with the data object. The methodcontinues at step 622 where the processing module encodes the data usinga dispersed storage error coding function utilizing first leveldispersal parameters to produce a plurality of sets of first levelencoded data slices. For each set of the first level encoded dataslices, the method continues at step 624 where the processing moduleoutputs the set of first level encoded data slices to a set ofdistributed storage and task (DST) processing units. The outputtingincludes generating a set of store data requests that the set of firstlevel encoded data slices.

Each DST processing unit of the set of DST processing units encodes acorresponding first level encoded data slice of the set of first levelencoded data slices using the dispersed storage error coding functionutilizing second level dispersal parameters to produce a plurality ofsets of second level encoded data slices for storage in a distributedstorage and task network (DSTN) module. Each DST processing unit of theset of DST processing units generates and outputs a storage responsethat includes one of a failure indicator and a indicator that a secondlevel dispersal parameter write threshold number of encoded data slicesof a corresponding second level set of encoded data slices has beensuccessfully stored in the DSTN module.

The method continues at step 626 where the processing module receivesstorage responses from at least some of the set of DST processing units.When receiving a first level dispersal parameter write threshold numberof favorable storage responses from a subset of the set of DSTprocessing units, the method continues at step 628 where the processingmodule generates and outputs a cancellation message to other DSTprocessing units of the set of DST processing units. The cancellationmessage includes at least one of a deletion request and a rollbackrequest. The method continues at step 630 where the processing moduleupdates a directory to include an association between the data ID of thedata, identifiers of the subset of the set of DST processing units, andidentifiers of a first level dispersal parameter write threshold numberof encoded data slices stored at the subset of the set of DST processingunits.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method comprises: sending, by a first device ofa dispersed storage network (DSN), a set of write revision requests tostorage units of the DSN, wherein a write revision request of the set ofwrite revision requests includes a slice name and a revision numbercorresponding to a revision level of a revised encoded data slice;generating, by one of the storage units, a write revision responseregarding a potential write conflict issue based on the revision number;receiving, by the first device, the write revision responses from atleast some of the storage units to produce a set of received writerevision responses; interpreting, by the first device, the set ofreceived write revision responses to determine whether a write conflictissue exists; when the write conflict issue exists, issuing, by thefirst device, a set of write roll back requests to the storage unitsregarding aborting storage of respective revised encoded data slices;and when the write conflict issue does not exist, issuing, by the firstdevice, a set of next phase write requests to the storage unitsregarding storing the respective revised encoded data slices.
 2. Themethod of claim 1, wherein the sending the set of write revisionrequests further comprises: including the revised encoded data slice ofthe respective revised encoded data slices in the write revisionrequest.
 3. The method of claim 1, wherein the issuing the set of nextphase write requests further comprises: including the revised encodeddata slice of the respective revised encoded data slices in one of theset of next phase write requests.
 4. The method of claim 1 furthercomprises: generating, by the one of the storage units, the writerevision response to include a list of revision numbers that correspondsto a number of revised encoded data slices having the slice name thatthe one of the storage units is storing; and interpreting, by the firstdevice, the lists of revision numbers of the set of received writerevision responses in view of the revision number by: comparing a mostrecent revision number of the lists of revision numbers to the revisionnumber; and when at least a decode threshold number of the lists ofrevision numbers compare favorably to the revision number, indicatingthat the write conflict issue does not exist.
 5. The method of claim 1further comprises: generating, by the one of the storage units, thewrite revision response to include a most recent revision numbercorresponding to a most recently stored one of the respective revisedencoded data slices; and interpreting, by the first device, the mostrecent revision numbers of the set of received write revision responsesin view of the revision number and when at least a decode thresholdnumber of the most recent revision numbers compare favorably to therevision number, indicating that the write conflict issue does notexist.
 6. The method of claim 1 further comprises: generating, by theone of the storage units, the write revision response to include afavorable or unfavorable revision number indication; and interpreting,by the first device, the set of received write revision responses byindicating that the write conflict issue does not exist when at least adecode threshold number of favorable revision number indications werereceived.
 7. The method of claim 6 further comprises: comparing, by theone of the storage units, a most recent revision number corresponding toa most recently stored one of the respective revised encoded data slicesto the revision number; when the most recent revision number is lessthan the revision number, indicating, by the one of the storage units,the favorable revision number indication; and when the most recentrevision number is greater than or equal to the revision number,indicating, by the one of the storage units, the unfavorable revisionnumber indication.
 8. The method of claim 1 further comprises: locking,by the one of the storage units, the slice name for a corresponding oneof the set of write revision requests; and while the slice name islocked for the corresponding one of the set of write revision requests:receiving, by the one of the storage units from a second device of theDSN, a second write revision request regarding the slice name; andsending, by the one of the storage units, a write error message to thesecond device.
 9. A dispersed storage network (DSN) comprises: a firstmodule, when operable within a first device of the DSN, causes the firstdevice to send a set of write revision requests to storage units of theDSN, wherein a write revision request of the set of write revisionrequests includes a slice name and a revision number corresponding to arevision level of a revised encoded data slice; a second module, whenoperable within one of the storage units, causes the one of the storageunits to generate a write revision response regarding a potential writeconflict issue based on the revision number; a third module, whenoperable within the first device, causes the first device to interpret aset of received write revision responses to determine whether a writeconflict issue exists, wherein the first device received the writerevision responses from at least some of the storage units to producethe set of received write revision responses; and a fourth module, whenoperable within the first device, causes the first device to: issue aset of write roll back requests to the storage units regarding abortingstorage of respective revised encoded data slices when the writeconflict issue exists; and issue a set of next phase write requests tothe storage units regarding storing the respective revised encoded dataslices when the write conflict issue does not exist.
 10. The DSN ofclaim 9, wherein the first module further functions to send the set ofwrite revision requests by: including the revised encoded data slice ofthe respective revised encoded data slices in the write revisionrequest.
 11. The DSN of claim 9, wherein the fourth module furtherfunctions to issue the set of next phase write requests by: includingthe revised encoded data slice of the respective revised encoded dataslices in one of the set of next phase write requests.
 12. The DSN ofclaim 9 further comprises: the second module functions to generate thewrite revision response to include a list of revision numbers thatcorresponds to a number of revised encoded data slices having the slicename that the one of the storage units is storing; and the third modulefunctions to interpret the lists of revision numbers of the set ofreceived write revision responses in view of the revision number by:comparing a most recent revision number of the lists of revision numbersto the revision number; and when at least a decode threshold number ofthe lists of revision numbers compare favorably to the revision number,indicating that the write conflict issue does not exist.
 13. The DSN ofclaim 9 further comprises: the second module functions to generate thewrite revision response to include a most recent revision numbercorresponding to a most recently stored one of the respective revisedencoded data slices; and the third module functions to interpret themost recent revision numbers of the set of received write revisionresponses in view of the revision number and when at least a decodethreshold number of the most recent revision numbers compare favorablyto the revision number, indicating that the write conflict issue doesnot exist.
 14. The DSN of claim 9 further comprises: the second modulefunctions to generate the write revision response to include a favorableor unfavorable revision number indication; and the third modulefunctions to interpret the set of received write revision responses byindicating that the write conflict issue does not exist when at least adecode threshold number of favorable revision number indications werereceived.
 15. The DSN of claim 14 further comprises: the second modulefurther functions to: compare a most recent revision numbercorresponding to a most recently stored one of the respective revisedencoded data slices to the revision number; indicate the favorablerevision number indication when the most recent revision number is lessthan the revision number; and indicate the unfavorable revision numberindication when the most recent revision number is greater than or equalto the revision number.
 16. The DSN of claim 9 further comprises: thesecond module further functions to: lock the slice name for acorresponding one of the set of write revision requests; and while theslice name is locked for the corresponding one of the set of writerevision requests: receive, from a second device of the DSN, a secondwrite revision request regarding the slice name; and send a write errormessage to the second device.